[BUG] Debug logger breaks during cuda.jit call when debugger was called before

[ZzEeKkAa]

Describe the bug

Debug logger breaks during cuda.jit call when debugger was called before

Steps/Code to reproduce bug

import numpy as np
from numba import cuda
import logging

logging.getLogger().setLevel(logging.DEBUG)


def main():
    logging.info("Start") # <- without this everything works

    @cuda.jit
    def f(a):
        a[0]=0

    a = np.zeros(1,dtype=np.float32)
    f[1, 1](a)


if __name__ == "__main__":
    main()

Results in an error log:

DEBUG:numba.core.byteflow:----------------------DONE Prune PHIs-----------------------
DEBUG:numba.core.byteflow:block_infos State(pc_initial=0 nstack_initial=0):
AdaptBlockInfo(insts=((0, {}), (2, {}), (4, {'res': '$const4.0.1'}), (6, {'res': '$a6.1'}), (8, {'res': '$const8.2.1'}), (10, {'target': '$a6.1', 'index': '$const8.2.1', 'value': '$const4.0.1'}), (12, {}), (14, {'res': '$const14.3.0'}), (16, {'retval': '$const14.3.0', 'castval': '$16return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})
--- Logging error ---
Traceback (most recent call last):
  File "/local/home/yhavrylko/opt/lib/python3.11/logging/__init__.py", line 1110, in emit
    msg = self.format(record)
          ^^^^^^^^^^^^^^^^^^^
  File "/local/home/yhavrylko/opt/lib/python3.11/logging/__init__.py", line 953, in format
    return fmt.format(record)
           ^^^^^^^^^^^^^^^^^^
  File "/local/home/yhavrylko/opt/lib/python3.11/logging/__init__.py", line 687, in format
    record.message = record.getMessage()
                     ^^^^^^^^^^^^^^^^^^^
  File "/local/home/yhavrylko/opt/lib/python3.11/logging/__init__.py", line 375, in getMessage
    msg = str(self.msg)
          ^^^^^^^^^^^^^
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/utils.py", line 788, in __str__
    return pformat(*self.args, **self.kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: pformat() got an unexpected keyword argument 'lazy_func'
Call stack:
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/nvmath-python/./examples/device/cublasdx_simple_gemm_fp32.py", line 22, in <module>
    f[1, 1](a)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/dispatcher.py", line 700, in __call__
    return self.dispatcher.call(
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/dispatcher.py", line 1022, in call
    kernel = _dispatcher.Dispatcher._cuda_call(self, *args)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/dispatcher.py", line 1030, in _compile_for_args
    return self.compile(tuple(argtypes))
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba/src/numba/core/compiler_lock.py", line 35, in _acquire_compile_lock
    return func(*args, **kwargs)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/dispatcher.py", line 1296, in compile
    kernel = _Kernel(self.py_func, argtypes, **self.targetoptions)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba/src/numba/core/compiler_lock.py", line 35, in _acquire_compile_lock
    return func(*args, **kwargs)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/dispatcher.py", line 145, in __init__
    cres = compile_cuda(
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba/src/numba/core/compiler_lock.py", line 35, in _acquire_compile_lock
    return func(*args, **kwargs)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/compiler.py", line 745, in compile_cuda
    cres = compile_extra(
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/compiler.py", line 586, in compile_extra
    return pipeline.compile_extra(func)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/core/compiler.py", line 124, in compile_extra
    return self._compile_bytecode()
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/core/compiler.py", line 192, in _compile_bytecode
    return self._compile_core()
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/core/compiler.py", line 160, in _compile_core
    pm.run(self.state)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/core/compiler_machinery.py", line 384, in run
    self._runPass(idx, pass_inst, state)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba/src/numba/core/compiler_lock.py", line 35, in _acquire_compile_lock
    return func(*args, **kwargs)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/core/compiler_machinery.py", line 336, in _runPass
    mutated |= check(pss.run_pass, internal_state)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/core/compiler_machinery.py", line 290, in check
    mangled = func(compiler_state)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/compiler.py", line 497, in run_pass
    func_ir = interp.interpret(bc)
  File "/home/scratch.yhavrylko_ent/Projects/nvidia/numba-cuda/numba_cuda/numba/cuda/core/interpreter.py", line 1431, in interpret
    _logger.debug(
Message: <numba.cuda.utils._lazy_pformat object at 0x7f7e0b5c1790>
Arguments: ()
DEBUG:numba.cuda.core.ssa:==== SSA block analysis pass on 0

Expected behavior

Works without error log

Environment details (please complete the following information):

• Environment location: Bare-metal, n/a
• Method of numba-cuda install: from source, pip, n/a

[gmarkall]

Does this reproduce for you on main? Can you give the output of numba -s so I can see what your environment is like? (This seems not to reproduce for me)

[ZzEeKkAa]

Does this reproduce for you on main? Can you give the output of numba -s so I can see what your environment is like? (This seems not to reproduce for me)

Yes, it does reproduce on main

numba -s                                                             ✔  nvmath-python   yhavrylko@marie  09:46:25 AM 
System info:
<frozen importlib._bootstrap_external>:1241: FutureWarning: The cuda.cuda module is deprecated and will be removed in a future release, please switch to use the cuda.bindings.driver module instead.
--------------------------------------------------------------------------------
__Time Stamp__
Report started (local time)                   : 2025-09-02 09:46:34.657443
UTC start time                                : 2025-09-02 16:46:34.657447
Running time (s)                              : 12.962441

__Hardware Information__
Machine                                       : x86_64
CPU Name                                      : znver2
CPU Count                                     : 64
Number of accessible CPUs                     : 64
List of accessible CPUs cores                 : 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
CFS Restrictions (CPUs worth of runtime)      : None

CPU Features                                  : 64bit adx aes avx avx2 bmi bmi2
                                                clflushopt clwb clzero cmov crc32
                                                cx16 cx8 f16c fma fsgsbase fxsr
                                                lzcnt mmx movbe mwaitx pclmul
                                                popcnt prfchw rdpid rdpru rdrnd
                                                rdseed sahf sha sse sse2 sse3
                                                sse4.1 sse4.2 sse4a ssse3 wbnoinvd
                                                xsave xsavec xsaveopt xsaves

Memory Total (MB)                             : 257601
Memory Available (MB)                         : 235047

__OS Information__
Platform Name                                 : Linux-5.8.0-53-generic-x86_64-with-glibc2.31
Platform Release                              : 5.8.0-53-generic
OS Name                                       : Linux
OS Version                                    : #60~20.04.1-Ubuntu SMP Thu May 6 09:52:46 UTC 2021
OS Specific Version                           : ?
Libc Version                                  : glibc 2.31

__Python Information__
Python Compiler                               : GCC 9.3.0
Python Implementation                         : CPython
Python Version                                : 3.11.13
Python Locale                                 : en_US.UTF-8

__Numba Toolchain Versions__
Numba Version                                 : 0.61.2+4.gae8dd6d8e
llvmlite Version                              : 0.44.0

__LLVM Information__
LLVM Version                                  : 15.0.7

__CUDA Information__
CUDA Target Implementation                    : NVIDIA
CUDA Device Initialized                       : True
CUDA Driver Version                           : 13.0
CUDA Runtime Version                          : 12.9
CUDA NVIDIA Bindings Available                : True
CUDA NVIDIA Bindings In Use                   : True
CUDA Minor Version Compatibility Available    : False
CUDA Minor Version Compatibility Needed       : False
CUDA Minor Version Compatibility In Use       : False
CUDA Detect Output:
Found 4 CUDA devices
id 0    b'NVIDIA RTX 6000 Ada Generation'                              [SUPPORTED]
                      Compute Capability: 8.9
                           PCI Device ID: 0
                              PCI Bus ID: 34
                                    UUID: GPU-9b7e8b2a-29c5-a146-cf92-6ff51c285e52
                                Watchdog: Disabled
             FP32/FP64 Performance Ratio: 64
id 1    b'NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition'                              [SUPPORTED]
                      Compute Capability: 12.0
                           PCI Device ID: 0
                              PCI Bus ID: 65
                                    UUID: GPU-8a25347a-d7a1-bd2e-d982-a83c73df94d2
                                Watchdog: Disabled
             FP32/FP64 Performance Ratio: 64
id 2     b'NVIDIA RTX A6000'                              [SUPPORTED]
                      Compute Capability: 8.6
                           PCI Device ID: 0
                              PCI Bus ID: 33
                                    UUID: GPU-d5f062a2-baf3-dc24-c7a2-11555c714e64
                                Watchdog: Disabled
             FP32/FP64 Performance Ratio: 64
id 3     b'NVIDIA RTX A6000'                              [SUPPORTED]
                      Compute Capability: 8.6
                           PCI Device ID: 0
                              PCI Bus ID: 67
                                    UUID: GPU-11b72959-d8f3-caac-e920-78d2a93ac773
                                Watchdog: Disabled
             FP32/FP64 Performance Ratio: 64
Summary:
        4/4 devices are supported

CUDA Libraries Test Output:
Finding driver from candidates:
        libcuda.so
        libcuda.so.1
        /usr/lib/libcuda.so
        /usr/lib/libcuda.so.1
        /usr/lib64/libcuda.so
        /usr/lib64/libcuda.so.1
Using loader <class 'ctypes.CDLL'>
        Trying to load driver...        ok
                Loaded from libcuda.so
        Mapped libcuda.so paths:
                /usr/lib/x86_64-linux-gnu/libcuda.so.580.40
Finding nvvm from NVIDIA NVCC Wheel
        Located at /home/scratch.yhavrylko_ent/Projects/nvidia/nvmath-python/.venv/lib/python3.11/site-packages/nvidia/cuda_nvcc/nvvm/lib64/libnvvm.so
        Trying to open library...       ok
Finding nvrtc from NVIDIA NVCC Wheel
        Located at /home/scratch.yhavrylko_ent/Projects/nvidia/nvmath-python/.venv/lib/python3.11/site-packages/nvidia/cuda_nvrtc/lib/libnvrtc.so.12
        Trying to open library...       ok
Finding cudadevrt from System
        Located at /usr/local/cuda/lib64/libcudadevrt.a
        Checking library...     ok
Finding libdevice from NVIDIA NVCC Wheel
        Located at /home/scratch.yhavrylko_ent/Projects/nvidia/nvmath-python/.venv/lib/python3.11/site-packages/nvidia/cuda_nvcc/nvvm/libdevice/libdevice.10.bc
        Checking library...     ok
Include directory configuration variable:
        CUDA_INCLUDE_PATH=/usr/local/cuda/include
Finding include directory from NVIDIA NVCC Wheel
        Located at /home/scratch.yhavrylko_ent/Projects/nvidia/nvmath-python/.venv/lib/python3.11/site-packages/nvidia/cuda_runtime/include
        Checking include directory...   ok


__NumPy Information__
NumPy Version                                 : 2.2.0
NumPy Supported SIMD features                 : ('MMX', 'SSE', 'SSE2', 'SSE3', 'SSSE3', 'SSE41', 'POPCNT', 'SSE42', 'AVX', 'F16C', 'FMA3', 'AVX2')
NumPy Supported SIMD dispatch                 : ('SSSE3', 'SSE41', 'POPCNT', 'SSE42', 'AVX', 'F16C', 'FMA3', 'AVX2', 'AVX512F', 'AVX512CD', 'AVX512_KNL', 'AVX512_KNM', 'AVX512_SKX', 'AVX512_CLX', 'AVX512_CNL', 'AVX512_ICL')
NumPy Supported SIMD baseline                 : ('SSE', 'SSE2', 'SSE3')
NumPy AVX512_SKX support detected             : False

__SVML Information__
SVML State, config.USING_SVML                 : False
SVML Library Loaded                           : False
llvmlite Using SVML Patched LLVM              : True
SVML Operational                              : False

__Threading Layer Information__
TBB Threading Layer Available                 : False
+--> Disabled due to Unknown import problem.
OpenMP Threading Layer Available              : True
+-->Vendor: GNU
Workqueue Threading Layer Available           : True
+-->Workqueue imported successfully.

__Numba Environment Variable Information__
None found.

__Conda Information__
Conda Build                                   : 25.7.0
Conda Env                                     : 25.7.0
Conda Platform                                : linux-64
Conda Python Version                          : 3.12.7.final.0
Conda Root Writable                           : True

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_openmp_mutex                4.5              2_gnu               conda-forge
archspec                     0.2.3            pyhd8ed1ab_0        conda-forge
attrs                        24.2.0           pyh71513ae_0        https://prefix.dev/conda-forge
beautifulsoup4               4.12.3           pyha770c72_0        https://prefix.dev/conda-forge
boltons                      24.0.0           pyhd8ed1ab_0        conda-forge
brotli-python                1.1.0            py312h2ec8cdc_2     conda-forge
bzip2                        1.0.8            h4bc722e_7          conda-forge
c-ares                       1.32.3           h4bc722e_0          conda-forge
ca-certificates              2025.8.3         hbd8a1cb_0          https://prefix.dev/conda-forge
certifi                      2025.8.3         pyhd8ed1ab_0        https://prefix.dev/conda-forge
cffi                         1.17.1           py312h06ac9bb_0     conda-forge
chardet                      5.2.0            py312h7900ff3_2     https://prefix.dev/conda-forge
charset-normalizer           3.4.0            pyhd8ed1ab_0        conda-forge
click                        8.1.7            unix_pyh707e725_0   https://prefix.dev/conda-forge
colorama                     0.4.6            pyhd8ed1ab_0        conda-forge
conda                        25.7.0           py312h7900ff3_0     https://prefix.dev/conda-forge
conda-build                  25.7.0           py312h7900ff3_0     https://prefix.dev/conda-forge
conda-index                  0.5.0            pyhd8ed1ab_0        https://prefix.dev/conda-forge
conda-libmamba-solver        25.3.0           pyhd8ed1ab_0        https://prefix.dev/conda-forge
conda-package-handling       2.4.0            pyh7900ff3_0        conda-forge
conda-package-streaming      0.11.0           pyhd8ed1ab_0        conda-forge
cpp-expected                 1.1.0            hf52228f_0          https://prefix.dev/conda-forge
distro                       1.9.0            pyhd8ed1ab_0        conda-forge
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filelock                     3.16.1           pyhd8ed1ab_0        https://prefix.dev/conda-forge
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frozendict                   2.4.6            py312h66e93f0_0     conda-forge
h2                           4.1.0            pyhd8ed1ab_0        conda-forge
hpack                        4.0.0            pyh9f0ad1d_0        conda-forge
hyperframe                   6.0.1            pyhd8ed1ab_0        conda-forge
idna                         3.10             pyhd8ed1ab_0        conda-forge
importlib_resources          6.4.5            pyhd8ed1ab_0        https://prefix.dev/conda-forge
jinja2                       3.1.4            pyhd8ed1ab_0        https://prefix.dev/conda-forge
jsonpatch                    1.33             pyhd8ed1ab_0        conda-forge
jsonpointer                  3.0.0            py312h7900ff3_1     conda-forge
jsonschema                   4.23.0           pyhd8ed1ab_0        https://prefix.dev/conda-forge
jsonschema-specifications    2024.10.1        pyhd8ed1ab_0        https://prefix.dev/conda-forge
keyutils                     1.6.1            h166bdaf_0          conda-forge
krb5                         1.21.3           h659f571_0          conda-forge
ld_impl_linux-64             2.43             h712a8e2_2          conda-forge
libarchive                   3.7.7            hadbb8c3_0          https://prefix.dev/conda-forge
libcurl                      8.12.1           h332b0f4_0          https://prefix.dev/conda-forge
libedit                      3.1.20191231     he28a2e2_2          conda-forge
libev                        4.33             hd590300_2          conda-forge
libexpat                     2.6.4            h5888daf_0          conda-forge
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libgcc                       14.2.0           h77fa898_1          conda-forge
libgcc-ng                    14.2.0           h69a702a_1          conda-forge
libgomp                      14.2.0           h77fa898_1          conda-forge
libiconv                     1.17             hd590300_2          conda-forge
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liblzma                      5.6.4            hb9d3cd8_0          https://prefix.dev/conda-forge
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lzo                          2.10             hd590300_1001       conda-forge
mamba                        2.0.7            h3f3603c_2          https://prefix.dev/conda-forge
markupsafe                   3.0.2            py312h178313f_0     https://prefix.dev/conda-forge
menuinst                     2.2.0            py312h7900ff3_0     conda-forge
more-itertools               10.5.0           pyhd8ed1ab_0        https://prefix.dev/conda-forge
ncurses                      6.5              he02047a_1          conda-forge
nlohmann_json                3.11.3           he02047a_1          https://prefix.dev/conda-forge
openssl                      3.5.1            h7b32b05_0          https://prefix.dev/conda-forge
packaging                    24.1             pyhd8ed1ab_0        conda-forge
patch                        2.7.6            h7f98852_1002       https://prefix.dev/conda-forge
patchelf                     0.17.2           h58526e2_0          https://prefix.dev/conda-forge
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pkgutil-resolve-name         1.3.10           pyhd8ed1ab_1        https://prefix.dev/conda-forge
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pysocks                      1.7.1            pyha2e5f31_6        conda-forge
python                       3.12.7           hc5c86c4_0_cpython  conda-forge
python-libarchive-c          5.1              py312h7900ff3_1     https://prefix.dev/conda-forge
python_abi                   3.12             5_cp312             conda-forge
pytz                         2024.2           pyhd8ed1ab_0        https://prefix.dev/conda-forge
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reproc                       14.2.5.post0     hb9d3cd8_0          https://prefix.dev/conda-forge
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requests                     2.32.3           pyhd8ed1ab_0        conda-forge
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tk                           8.6.13           noxft_h4845f30_101  conda-forge
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xz                           5.2.6            h166bdaf_0          conda-forge
yaml                         0.2.5            h7f98852_2          https://prefix.dev/conda-forge
yaml-cpp                     0.8.0            h59595ed_0          conda-forge
zipp                         3.21.0           pyhd8ed1ab_0        https://prefix.dev/conda-forge
zstandard                    0.23.0           py312h66e93f0_1     https://prefix.dev/conda-forge
zstd                         1.5.7            hb8e6e7a_1          https://prefix.dev/conda-forge

No errors reported.


No warnings reported.

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It looks like report is not accurate. I'm not in the conda environment, but I have conda environment with the same name (I'm pretty sure it is not the cause)

pip list
Package                       Version             Editable project location
----------------------------- ------------------- --------------------------------------------------------------------------------
accessible-pygments           0.0.5
alabaster                     1.0.0
anyio                         4.9.0
apeye                         1.4.1
apeye-core                    1.1.5
argon2-cffi                   25.1.0
argon2-cffi-bindings          21.2.0
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[acosmicflamingo]

The problem originated during the vendoring in of some core functionality last year to this codebase. In this PR, I noticed that there wasn't any mention of a utils.py file, which is where the _lazy_pformat class resides. Given that it was working for @gmarkall but not @ZzEeKkAa, after doing some sleuthing and analyzing the commit history of this codebase and upstream's, I noticed that there was a change involving lazy_func that was introduced in Februrary of 2025 that didn't seem to appear in numba_cuda/numba/cuda/utils.py. So I think @gmarkall must've had the upstream numba installed and @ZzEeKkAa had numba-cuda installed.

I have created a PR with the fixes (that I got from Todd Anderson's commit) here.